Transmission of voice by digital techniques has become widespread and incorporated into a wide range of devices, including, wireless communication devices, personal digital assistants (PDAs), laptop computers, desktop computers, mobile and or satellite ratio telephones, and the like. This, in turn, has created interest in determining the least amount of information that can be sent over a channel while maintaining the perceived quality of the reconstructed speech. If speech is transmitted by simply sampling and digitizing, a data rate on the order of sixty-four kilobits per second (kbps) may be required to achieve a speech quality of conventional analog telephone. However, through the use of speech analysis, followed by an appropriate coding, transmission, and resynthesis at the receiver, a significant reduction in the data rate can be achieved. Devices for compressing speech find use in many fields of telecommunications. An exemplary field is wireless communications. The field of wireless communications has many applications including, e.g., cordless telephones, paging, wireless local loops, wireless telephony such as cellular and PCS telephone systems, mobile Internet Protocol (IP) telephony, and satellite communication systems. A particularly important application is wireless telephony for mobile subscribers.
Various over-the-air interfaces have been developed for wireless communication systems including, e.g., frequency division multiple access (FDMA), time division multiple access (TDMA), and code division multiple access (CDMA). In connection therewith, various domestic and international standards have been established including, e.g., Advanced Mobile Phone Service (AMPS), Global System for Mobile Communications (GSM), and Interim Standard 95 (IS-95). An exemplary wireless telephony communication system is a code division multiple access (CDMA) system. The IS-95 standard and its derivatives, IS-95A, ANSI J-STD-008, and IS-95B (referred to collectively herein as IS-95), are promulgated by the Telecommunication Industry Association (TIA) and other well-known standards bodies to specify the use of a CDMA over-the-air interface for cellular or PCS telephony communication systems. Exemplary wireless communication systems configured substantially in accordance with the use of the IS-95 standard are described in U.S. Pat. Nos. 5,103,459 and 4,901,307.
The IS-95 standard subsequently evolved into “3G” systems, such as cdma2000 and WCDMA, which provide more capacity and high speed packet data services. Two variations of cdma2000 are presented by the documents IS-2000 (cdma2000 1xRTT) and IS-856 (cdma2000 1xEV-DO), which are issued by TIA. The cdma2000 1xRTT communication system offers a peak data rate of 153 kbps whereas the cdma2000 1xEV-DO communication system defines a set of data rates, ranging from 38.4 kbps to 2.4 Mbps. The WCDMA standard is embodied in 3rd Generation Partnership Project “3GPP”, Document Nos. 3G TS 25.211, 3G TS 25.212, 3G TS 25.213, and 3G TS 25.214.
Devices that employ techniques to compress speech by extracting parameters that relate to a model of human speech generation are called speech coders. Speech coders typically comprise an encoder and a decoder. Speech codecs are a type of speech coder and do comprise an encoder and a decoder. The encoder divides the incoming speech signal into blocks of time, or analysis frames. The duration of each segment in time (or “frame”) is typically selected to be short enough that the spectral envelope of the signal may be expected to remain relatively stationary. For example, one typical frame length is twenty milliseconds, which corresponds to 160 samples at a typical sampling rate of eight kilohertz (kHz), although any frame length or sampling rate deemed suitable for the particular application may be used.
The encoder analyzes the incoming speech frame to extract certain relevant parameters, and then quantizes the parameters into binary representation, i.e., to a set of bits or a binary data packet. The data packets are transmitted over the communication channel (i.e., a wired and/or wireless network connection) to a receiver and a decoder. The decoder processes the data packets, unquantizes them to produce the parameters, and resynthesizes the speech frames using the unquantized parameters.
The function of the speech coder is to compress the digitized speech signal into a low-bit-rate signal by removing natural redundancies inherent in speech. The digital compression is achieved by representing the input speech frame with a set of parameters and employing quantization to represent the parameters with a set of bits. If the input speech frame has a number of bits Ni and the data packet produced by the speech coder has a number of bits No, the compression factor achieved by the speech coder is Cr=Ni/No. The challenge is to retain high voice quality of the decoded speech while achieving the target compression factor. The performance of a speech coder depends on (1) how well the speech model, or the combination of the analysis and synthesis process described above, performs, and (2) how well the parameter quantization process is performed at the target bit rate of No bits per frame. The goal of the speech model is thus to capture the essence of the speech signal, or the target voice quality, with a small set of parameters for each frame.
Perhaps most important in the design of a speech coder is the search for a good set of parameters (including vectors) to describe the speech signal. A good set of parameters requires a low system bandwidth for the reconstruction of a perceptually accurate speech signal. Pitch, signal power, spectral envelope (or formants), amplitude and phase spectra are examples of the speech coding parameters.
Speech coders may be implemented as time-domain coders, which attempt to capture the time-domain speech waveform by employing high time-resolution processing to encode small segments of speech (typically 5 millisecond (ms) subframes) at a time. For each subframe, a high-precision representative from a codebook space is found by means of various search algorithms known in the art. Alternatively, speech coders may be implemented as frequency-domain coders, which attempt to capture the short-term speech spectrum of the input speech frame with a set of parameters (analysis) and employ a corresponding synthesis process to recreate the speech waveform from the spectral parameters. The parameter quantizer preserves the parameters by representing them with stored representations of code vectors in accordance with known quantization techniques.
A well-known time-domain speech coder is the Code Excited Linear Predictive (CELP) coder described in L. B. Rabiner & R. W. Schafer, Digital Processing of Speech Signals 396-453 (1978). In a CELP coder, the short-term correlations, or redundancies, in the speech signal are removed by a linear prediction (LP) analysis, which finds the coefficients of a short-term formant filter. Applying the short-term prediction filter to the incoming speech frame generates an LP residue signal, which is further modeled and quantized with long-term prediction filter parameters and a subsequent stochastic codebook. Thus, CELP coding divides the task of encoding the time-domain speech waveform into the separate tasks of encoding the LP short-term filter coefficients and encoding the LP residue. Time-domain coding can be performed at a fixed rate (i.e., using the same number of bits, No, for each frame) or at a variable rate (in which different bit rates are used for different types of frame contents). Variable-rate coders attempt to use only the amount of bits needed to encode the codec parameters to a level adequate to obtain a target quality. An exemplary variable rate CELP coder is described in U.S. Pat. No. 5,414,796.
Time-domain coders such as the CELP coder typically rely upon a high number of bits, N0, per frame to preserve the accuracy of the time-domain speech waveform. Such coders typically deliver excellent voice quality provided that the number of bits, N0, per frame is relatively large (e.g., 8 kbps or above). However, at low bit rates (e.g., 4 kbps and below), time-domain coders fail to retain high quality and robust performance due to the limited number of available bits. At low bit rates, the limited codebook space clips the waveform-matching capability of conventional time-domain coders, which are so successfully deployed in higher-rate commercial applications. Hence, despite improvements over time, many CELP coding systems operating at low bit rates suffer from perceptually significant distortion typically characterized as noise.
An alternative to CELP coders at low bit rates is the “Noise Excited Linear Predictive” (NELP) coder, which operates under similar principles as a CELP coder. However, NELP coders use a filtered pseudo-random noise signal to model speech, rather than a codebook. Since NELP uses a simpler model for coded speech, NELP achieves a lower bit rate than CELP. NELP is typically used for compressing or representing unvoiced speech or silence.
Coding systems that operate at rates on the order of 2.4 kbps are generally parametric in nature. That is, such coding systems operate by transmitting parameters describing the pitch-period and the spectral envelope (or formants) of the speech signal at regular intervals. Illustrative of these so-called parametric coders is the LP vocoder system. Some speech codecs are referred to as vocoders. Vocoders comprise an encoder and a decoder for compressing speech.
LP vocoders model a voiced speech signal with a single pulse per pitch period. This basic technique may be augmented to include transmission information about the spectral envelope, among other things. Although LP vocoders provide reasonable performance generally, they may introduce perceptually significant distortion, typically characterized as buzz.
In recent years, coders have emerged that are hybrids of both waveform coders and parametric coders. Illustrative of these so-called hybrid coders is the prototype-waveform interpolation (PWI) speech coding system. The PWI coding system may also be known as a prototype pitch period (PPP) speech coder. A PWI coding system provides an efficient method for coding voiced speech. The basic concept of PWI is to extract a representative pitch cycle (the prototype waveform) at fixed intervals, to transmit its description, and to reconstruct the speech signal by interpolating between the prototype waveforms. The PWI method may operate either on the LP residual signal or the speech signal. An exemplary PWI, or PPP, speech coder is described in U.S. Pat. No. 6,456,964, entitled PERIODIC SPEECH CODING. Other PWI, or PPP, speech coders are described in U.S. Pat. No. 5,884,253 and W. Bastiaan Kleijn & Wolfgang Granzow, Methods for Waveform Interpolation in Speech Coding, in Digital Signal Processing 215-230 (1991).
There is presently a surge of research interest and strong commercial need to develop a high-quality speech coder operating at medium to low bit rates (i.e., in the range of 2.4 to 4 kbps and below). The application areas include wireless telephony, satellite communications, Internet telephony, various multimedia and voice-streaming applications, voice mail, and other voice storage systems. The driving forces are the need for high capacity and the demand for robust performance under packet loss situations. Various recent speech coding standardization efforts are another direct driving force propelling research and development of low-rate speech coding algorithms. A low-rate speech coder creates more channels, or users, per allowable application bandwidth, and a low-rate speech coder coupled with an additional layer of suitable channel coding can fit the overall bit-budget of coder specifications and deliver a robust performance under channel error conditions.
One effective technique to encode speech efficiently at low bit rates is multimode coding. An exemplary multimode coding technique is described in U.S. Pat. No. 6,691,084, entitled VARIABLE RATE SPEECH CODING. Conventional multimode coders apply different modes, or encoding-decoding algorithms, to different types of input speech frames. Each mode, or encoding-decoding process, is customized to optimally represent a certain type of speech segment, such as, e.g., voiced speech, unvoiced speech, transition speech (e.g., between voiced and unvoiced), and background noise (nonspeech) in the most efficient manner. An external, open-loop mode decision mechanism examines the input speech frame and makes a decision regarding which mode to apply to the frame. The open-loop mode decision is typically performed by extracting a number of parameters from the input frame, evaluating the parameters as to certain temporal and spectral characteristics, and basing a mode decision upon the evaluation. The mode decision is thus made without knowing in advance the exact condition of the output speech, i.e., how close the output speech will be to the input speech in terms of voice quality or other performance measures.
As an illustrative example of multimode coding, a variable rate coder may be configured to perform CELP, NELP, or PPP coding of audio input according to the type of speech activity detected in a frame. If transient speech is detected, then the frame may be encoded using CELP. If voiced speech is detected, then the frame may be encoded using PPP. If unvoiced speech is detected, then the frame may be encoded using NELP. However, the same coding technique can frequently be operated at different bit rates, with varying levels of performance. Different coding techniques, or the same coding technique operating at different bit rates, or combinations of the above may be implemented to improve the performance of the coder.
Skilled artisans will recognize that increasing the number of encoder/decoder modes will allow greater flexibility when choosing a mode, which can result in a lower average bit rate. The increase in the number of encoder/decoder modes will correspondingly increase the complexity within the overall system. The particular combination used in any given system will be dictated by the available system resources and the specific signal environment.
In spite of the flexibility offered by the new multimode coders, the current multimode coders are still reliant upon coding bit rates that are fixed. In other words, the speech coders are designed with certain pre-set coding bit rates, which result in average output rates that are at fixed amounts.
Accurate ways to decide if the current encoding mode and/or encoding rate may provide good sound quality before the user hears the reconstructed speech signal has been a challenge in speech encoders for many years. A robust solution is desired.